40 ‘wild’ years: the current reality and future potential of assisted reproductive technologies in wildlife species
Bibliographic record
Abstract
Over the past 40 years, assisted reproductive technologies (ARTs) have grown significantly in scale and innovation, from the bovine embryo industry's shift from in vivo derived to in vitro produced embryos and the development of somatic cell-based approaches for embryo production. Domestic animal models have been instrumental in the development of ARTs for wildlife species in support of the One Plan Approach to species conservation that integrates in situ and ex situ population management strategies. While ARTs are not the sole solution to the biodiversity crisis, they can offer opportunities to maintain, and even improve, the genetic composition of the captive and wild gene pools over time. This review focuses on the application of sperm and embryo technologies (artificial insemination and multiple ovulation/in vitro produced embryo transfer, respectively) in wildlife species, highlighting impactful cases in which significant progress or innovation has transpired. One of the key messages following decades of efforts in this field is the importance of collaboration between researchers and practitioners from zoological, academic, governmental, and private sectors.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".